#AI Reads Urine#Urinary metabolic pattern for discriminating prostate cancer from benign prostatic hyperplasia
Published 21 July, 2025
The document mainly describes a study on urinary metabolomics of prostate diseases in the Chinese population, aiming to distinguish prostate cancer, benign prostatic hyperplasia, and non-prostate diseases by analyzing metabolites in urine.
The study recruited Chinese participants with prostate cancer, benign prostatic hyperplasia, and non-prostate diseases, collected their urine samples, and used four ultra-performance liquid chromatography/tandem mass spectrometric (UPLC-MS/MS) methods to detect the samples and analyze the changes in metabolites.
The results showed that patients with prostatic hyperplasia had significant abnormalities in lipid or amino acid metabolites, especially involving pathways such as histidine metabolism, purine metabolism, tryptophan metabolism, and tyrosine metabolism. In terms of distinguishing benign prostatic hyperplasia from prostate cancer, in addition to the previously reported metabolites related to phospholipid metabolism or tryptophan metabolism, metabolites such as dipeptides and androgenic steroids (e.g., leucylhydroxyproline and etiocholanolone glucuronide) also had potential distinguishing ability.
In conclusion, this study accurately detected the urinary metabolic patterns of patients with benign prostatic hyperplasia or prostate cancer, and these findings may provide potential biomarkers for distinguishing these two diseases. However, the study also has some limitations, such as the sample size can be further expanded. In the future, larger sample sizes and more accurate detection platforms are needed to verify the actual effect of these potential biomarkers in the diagnosis of prostate cancer.
Front Oncol. 2025 Jun 25:15:1604169. doi: 10.3389/fonc.2025.1604169.
Untargeted metabolomics revealed urinary metabolic pattern for discriminating prostate cancer from benign prostatic hyperplasia in Chinese participants
Youhe Gao
Statement: During the preparation of this work the author(s) used Doubao / AI reading for summarizing the content. After using this tool/service, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the published article.
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